Diagnostic Methods and Markers for Bacterial Vaginosis

ABSTRACT

A method of diagnosing bacterial vaginosis in a woman, which involves determining an amount of each of more than one BV-associated bacterium in a vaginal sample obtained from the female and assessing a BV status of the female based on the amount of each of the more than one BV-associated bacterium in the sample

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/590,515, filed May 9, 2018, which is a continuation of U.S. patentapplication Ser. No. 15/454,450, filed Mar. 9, 2017, which is acontinuation of U.S. patent application Ser. No. 14/712,137, filed May14, 2015, now U.S. Pat. No. 9,624,552, issued Apr. 18, 2017, which is acontinuation of U.S. patent application Ser. No. 13/771,550, filed Feb.20, 2013, now U.S. Pat. No. 9,057,111, issued Jun. 16, 2015, whichclaims the benefit of priority of U.S. Provisional Application Ser. No.61/600,845, filed Feb. 20, 2012. All of the foregoing patents andapplication and incorporated herein by reference in their entirety.

FIELD

The methods described herein are in the general field of clinicaltesting, including the field of diagnosing and monitoring of diseasesand conditions.

BACKGROUND

One of the common conditions experienced by women throughout their livesis vaginitis, which is typically characterized in the medical field asan inflammation of the vagina that can result in discharge, itching andpain. There are several potential etiologies of vaginitis, includingcandidal vaginitis, typically caused by overgrowth with the commensalfungal organism Candida albicans, trichomonal vaginitis, which is asexually transmitted infection (STI) caused by a protozoan parasiteTrichomonas vaginalis, vaginal atrophy, or atrophic vaginitis, whichresults from reduced estrogen levels during menopause, and bacterialvaginosis or vaginitis, which is associated with a perturbation in thein the composition of the bacterial microflora of the vagina. Vaginitissymptoms may include change in color, odor or amount of discharge from awoman's vagina, vaginal itching or irritation, pain during intercourse,painful urination, and light vaginal bleeding or spotting. Vaginitissymptoms can lead to various degrees of physical and emotionaldiscomfort, and lower the overall quality of life. Vaginitis symptomscan also be a sign of an underlying infection, which should be promptlyidentified and treated in order to avoid medical complications, and, incase of an STI, to avoid further transmission.

SUMMARY

The terms “invention,” “the invention,” “this invention” and “thepresent invention” used in this patent are intended to refer broadly toall of the subject matter of this patent and the patent claims below.Statements containing these terms should be understood not to limit thesubject matter described herein or to limit the meaning or scope of thepatent claims below. Covered by the patent embodiments of the inventionare defined by the claims, not this summary. This summary is ahigh-level overview of various aspects of the invention and introducessome of the concepts that are further described in the DetailedDescription section below. This summary is not intended to identify keyor essential features of the claimed subject matter, nor is it intendedto be used in isolation to determine the scope of the claimed subjectmatter. The subject matter should be understood by reference toappropriate portions of the entire specification, any or all drawingsand each claim.

Provided herein are improved methods useful for diagnosing bacterialvaginosis which can be also referred to in this patents as BV diagnosticmethods, tests or assays, or other similar terms. BV diagnostic methodsof the present invention are probative for vaginal microfloraalterations underlying BV, and use objective quantitative measures ofbacterial occurrence in vaginal samples. The improved BV diagnosticmethods are accurate, cost-effective, clinically predictive and readilyinterpretable. Generally, the improved BV diagnostic methods describedherein use appropriate analytical procedures to detect and quantifymolecular markers from several categories of bacteria in a vaginalsample. For example, the improved BV diagnostic methods of the presentinvention can use quantitative or semi-quantitative assays for detectionof bacterial DNA sequences, such as quantitative PCR, semi-quantitativePCR or direct nucleic acid detection assays, in order to quantitativelyor semi-quantitatively detect DNA sequences characteristic of severalbacterial categories in a vaginal sample. The categories of bacteriaquantitatively detected by the improved methods can be bacterial speciesor genera.

Categories of bacteria, also referred to as bacterial markers, areselected for detection by the BV diagnostic methods of the presentinvention in such a way as to provide a clinically meaningfulassessment, based on the results of detection, of the likelihood of BVin a woman from whom the vaginal sample was obtained. The improved BVdiagnostic methods interrogate vaginal samples for the presence of morethan one bacterial marker, and derive a combined result from thosemarkers that directly correlates with the presence or absence of BV. Thebacterial markers are selected for the improved BV diagnostic methods ofthe present invention based on their probative value, when the markersare used collectively, for this assessment of BV status of a vaginalsample. Some embodiments of the BV diagnostic methods described hereinadvantageously employ at least one marker that has high specificity withrespect to BV detection in a patient population, and at least one markerthat has high sensitivity with respect to BV detection in a patientpopulation. The selection of the bacterial markers used in the improvedBV diagnostic methods can vary and can be based on a number of factors,such as the health risks associated with particular markers or certainpatient characteristics, such as pregnancy or HIV status, as well as BVprevalence in a patient population. The methods and procedures forselecting the bacterial markers to be used in the BV diagnostic methodsare included within the scope of the present invention, as well as thecombinations of bacterial markers described herein used for diagnosing,predicting or assessing BV in a patient.

The improved BV diagnostic methods of the present in inventioncharacterize the bacterial markers detected in a sample using a scoringmethod, which is then translated into a clinical interpretation of a BVstatus of the sample. The scoring method used in the improved BVdiagnostic methods assigns scores to individual bacterial markers andgenerates a composite score when more than one bacterial marker is used.The scoring method uses the data on distribution of the levels of BVmarker organisms in a patient population in order to divide thepopulation into the categories characterized by scores reflecting thelevels of the marker in each category. The scoring method used in theimproved BV diagnostic methods is included within the scope of thepresent invention.

Among other things, described herein is a method of diagnosing bacterialvaginosis in a female, comprising: determining an amount of more thanone BV-associated bacterium in a sample obtained from the female; and,assessing a BV status of the female based on the amount of each of themore than one BV-associated bacterium in the sample. In one embodimentof the method, the more than one BV-associated bacterium is threebacteria. In one more embodiment of the method, more than oneBV-associated bacterium includes Atopobium vaginae, BVAB-2, andMegasphaera-1. In another embodiment of the method, the more than oneBV-associated bacterium also includes Gardnerella vaginalis. In analternative embodiment, more than one BV-associated bacterium does notinclude Gardnerella vaginalis. In yet another embodiment, the more thanone BV-associated bacterium does not include a Lactobacillus bacterium.In an alternative embodiment, the more than one BV-associated bacteriumincludes a Lactobacillus bacterium. In a variation of the aboveembodiments, the Lactobacillus bacterium is Lactobacillus crispatus.

One embodiment of the diagnostic methods described herein is a method ofdiagnosing bacterial vaginosis in a female, comprising: determining anamount of at least Atopobium vaginae, BVAB-2 or Megasphaera-1 in asample obtained from the female; and, assessing a BV status of thefemale based on the amount of each of the more than one BV-associatedbacterium in the sample, wherein an increased amount of one or more ofAtopobium vaginae, BVAB-2 or Megasphaera-1 indicates an increasedprobability of the female having BV. An amount of the Lactobacillusbacterium in the sample can also be determined, wherein an increasedamount of the Lactobacillus bacterium indicates a decreased probabilityof the female having bacterial vaginosis.

In some of the diagnostic methods according to the present invention,the step of determining comprises detection of DNA sequences from theeach of the more than one BV-associated bacterium. The detection of DNAsequences can be performed by quantitative PCR, semi-quantitative PCR ordirect DNA probe detection. Methods of detecting bacterial vaginosis inpregnant females are included within the scope of the present invention.

The methods of the present invention provide reproducible and objectiveways of evaluating vaginal microflora in women with signs and symptomsof vaginitis, and are at least comparable in diagnostic accuracy to theconventional gold standard for diagnosis of BV. The methods of thepresent invention employ simple and robust scoring systems and methodsthat allow for accurate differentiation of BV positive and negativesamples to be performed in a standardized and cost-effective manner. Anexemplary embodiment of a method of diagnosing bacterial vaginosis in afemale, comprises: determining an amount of each of more than oneBV-associated bacterium in a sample obtained from the female; assigninga score to the sample based on the amount of each of the more than oneBV-associated bacterium detected in the sample, and, assessing the BVstatus of the female based on the score assigned to the sample. The stepof assigning the score can comprise generating an individual score foreach of the more than one BV-associated bacterium detected in the samplebased on the amount of the each of the more than one BV-associatedbacterium; and, calculating the combined score from the individualscores.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a bar graph illustrating frequency distribution of Atopobiumvaginae (panel A), BVAB-2 (panel B) and Megasphaera-1 (panel C) in theeach of the three Nugent categories of the samples of the first samplegroup (as discussed in the working examples). Vertical axis showsorganism concentration as determined by qPCR. Positions of cut-offcalibrators or values, denoted as Cal-1 (a) and Cal-2(b), with respectto the organism concentrations are shown by horizontal lines.

FIG. 2 is a scheme illustrating interpretation of the results of thequantitative testing using composite score based on the individualscores for A. vaginae, BVAB-2 and Megasphaera-1.

DETAILED DESCRIPTION

Treatment for vaginitis is determined based on its causes and origins ina particular patient. For example, fungal vaginitis should be treated byan anti-fungal medication, applied topically or taken in an oral form,while trichomoniasis is treated by a different type of antibioticmedication (typically oral metronidazole or tinidazole). Estrogen, inthe form of vaginal creams, tablets or rings, is often prescribed totreat atrophic vaginitis, while BV may be treated by anti-bacterialmedications, including the antibiotics metronidazole and clindamycin.Some forms of vaginitis are a result of irritation of vaginal lining bycommon consumer products, such as soaps or lubricants, or particulartypes of undergarment, and the treatment may be as simple as stoppingthe use of an irritating product.

Since vaginitis has a variety of underlying causes, it is important toidentify the cause in order to determine correct treatment. Aninappropriate choice of treatment may not only delay the relief of thevaginitis symptoms in a woman, but also lead to medical complicationsand spread of an infection to the woman's sexual partners. Choosing aninappropriate drug for vaginitis (for example, an anti-fungal medicationfor BV, metronidazole for fungal infection, or an antibiotic for afungal infection) may lead to unnecessary side effects and cause drugresistance. Delayed diagnosis and inappropriate choice of treatment canalso result in emotional and financial losses for the woman, elevatedtreatment costs, and generally contribute to increases in healthcarespending and inefficiencies in healthcare delivery.

Whilst the presence of specific symptoms can sometimes be instructive indetermining an etiology, misdiagnosis is common. Diagnostic proceduresby a qualified practitioner are typically required to detect whether aninfection is present, and to determine the nature of the infection.Diagnostic procedures often include microscopy, usually of a vaginal wetmount sample, and culture of the vaginal discharge. The color,consistency, acidity, and other characteristics of the discharge may bepredictive of the causative agent. However, definitive identification ofinfectious organisms is very important for the successful treatment,because women may have more than one infection, or have symptoms thatoverlap with those of another infection.

Bacterial vaginosis (BV), one of the possible causes of vaginitis, is acondition marked by an imbalance in vaginal flora. Although the preciseetiology and pathophysiology of BV is not fully understood, thissyndrome accounts, by some estimates, for about 22 to 50% of vaginitissymptoms. BV has been linked to a variety of serious health risks forthe woman herself and others. For example, BV has been linked toincreased chances of preterm labor and delivery, which increases thechances of the woman's baby dying or having serious medical problems. BVwas also linked to pelvic inflammatory diseases (PID), a condition inwhich bacteria infect the uterus and/or fallopian tubes. PID can causeinfertility or damage the fallopian tubes, thus increasing the chancesof ectopic pregnancy, a life-threatening condition. Some studies showedthat pregnant women with BV are more likely to contract infectionsfollowing genital surgery, such as hysterectomy or an abortion. BV hasalso been linked to increased susceptibility to HIV infection afterexposure to HIV virus, increased risk of transmission of HIV, as well asan increased susceptibility to other STIs, such as herpes simplex virus(HSV), Chlamydia trachomatis, and Neisseria gonorrhoeae.

While many questions remain about the role of different bacterialspecies in BV causation, current BV theories explain the condition asreplacement of the normal, homogeneous, vaginal microflora (dominatedtypically by hydrogen-peroxide producing lactobacilli) with aheterogeneous mix of anaerobic and microaerophilic organisms. Diagnosisof BV has thus been defined by techniques that attempt to eitheridentify this shift in bacterial composition, or assess the concomitantimpact of this shift on non-microbiological indicators of vaginalhealth, or a combination of both of these approaches.

The standards against which diagnostic tests for BV are compared includethe so-called Amsel criteria and the Nugent Gram-stain scoring system.BV diagnosis under the Amsel criteria requires that at least three offour of the following criteria are met for a given patient:characteristic vaginal discharge; vaginal pH>4.5; positive amine test,meaning release of a primary amine (fishy) odor from a vaginal sample onthe addition of the KOH, and >20% of the epithelial cells present on thewet mount slide of the vaginal discharge being identified as ‘cluecells’ (meaning they are coated with small Gram-variable coccobacilliconsistent with the organism Gardnerella vaginalis). While still widelytouted as a useful diagnostic approach, the Amsel criteria are notcommonly used in routine practice, and since this method requiresinnately subjective evaluations of samples, wide fluctuations inaccuracy have been reported. Under optimal circumstances, Amsel-baseddiagnosis of BV is generally regarded in the medical field as arelatively specific but somewhat insensitive method for identifyingpatients with BV.

The Nugent Gram-stain scoring system, which was more recently developedthan the Amsel criteria, involves assessment of a normally prepared Gramstain for relative abundance of three morphotypes of bacteria, and thencalculating the so-called Nugent score based on the amounts of largeGram-positive rods (Lactobacilli morphotype; decrease in Lactobacilli isscored as 0 to 4), small Gram-negative and variable rods (Bacteroidesand Gardnerella morphotype; scored as 0 to 4), and curved gram-variablerods (Mobiluncus spp. morphotype; scored as 0 to 2). The Nugent scorecan range from 0 to 10, with scores of 0-3 deemed normal (non-BV), 4-6intermediate, and 7-10 positive for BV. The Nugent scoring system issomewhat more objective than the Amsel criteria, and is regarded as amore reproducible and predictive means of diagnosing BV. However, Nugentscoring still requires preparation and evaluation of slides, and isdependent on the skill of the slide reader. In addition to beinggenerally subjective, since many of the key morphotypes are difficult todifferentiate from non-contributory organisms of similar appearance,quantitative Gram-stain examination is laborious and impractical forroutine clinical use, and intermediate scores of uncertain clinicalsignificance are reported in 10-25% of samples tested.

Cultures of vaginal samples have not proven useful for diagnosing BV.Since a hallmark of the condition is a complex perturbation of thenormal vaginal microflora, culture-based identification of single‘marker’ organisms lacks both sensitivity and specificity. Many putativeBV-associated organisms, such as Gardnerella vaginalis, Mobiluncus spp.,Mycoplasma hominis, or Bacteroides spp., can comprise variable fractionsof the vaginal microflora in women without BV, compromising thespecificity of culture-based testing. In addition, many of the keyorganisms associated with BV are obligate anaerobes and either difficultto recover or unrecoverable using conventional culture methods, whichmakes a true evaluation of vaginal microflora by culture impossible.

A more current diagnostic approach is the use of tests designed todetect BV-related organisms, directly or indirectly. One so-called“indirect” approach is the BV Blue® test (Gryphus diagnostics, LLC). TheBV Blue test detects sialidase activity, an enzyme produced byBV-associated bacteria such as Gardnerella vaginalis, Bacteroides spp.,Prevotella spp., and Mobiluncus spp. In the test procedure, a vaginalfluid sample is placed in the test vessel which contains a chromogenicsubstrate for sialidase. After incubation, a developer solution isadded, and If the sample contained a high level of sialidase, a blue orgreen color is seen. Samples containing no sialidase, or low levels ofthis enzyme, will generate a yellow color in the reaction. The BV testis claimed to have high specificity and sensitivity, but has a number oflimitations. For example, specimens from the BV Blue test have to becollected from the lower one-third of the vaginal wall, because cervicalsialidase activity may give a false positive test result. Variousvaginal products, such as creams, ointments, spermicides or vaginallubricants, used by patients, may interfere with the enzymatic reaction.In addition, samples have to either tested immediately upon collection,or stored and transported under specific conditions to prevent loss ofenzymatic activity.

The Affirm® Microbial Identification Test (Beckton Dickinson) (“Affirmtest”) is an example of a direct specimen DNA probe-based diagnostictest for the differential detection and identification of the threetypes of vaginitis causative organisms: Candida spp., G. vaginalis andT. vaginalis. The Affirm test is convenient for a clinician, since itoffers the results for three different organisms from a single sample.For BV diagnosis, the test relies on the detection of elevatedconcentrations of G. vaginalis. While the Affirm test offers the abilityto improve the accuracy and objectivity of vaginitis diagnosis, and isnot as prone to external interferences as the BV Blue test, it is alsoknown to be less specific than the Nugent Gram-stain scoring approach.

One unresolved issue with the Affirm assay is that it relies on thenotion that G. vaginalis functions as a uniquely predictive marker forBV, a concept known not to be accurate in the medical field. A morenuanced (and commonly accepted) view of BV in the field is that thehallmark of this condition is an increase in the diversity of thevaginal microbiome, with the composition of the BV-associated florabeing highly complex, and lacking a single ‘signature’ organism Whilstelevated levels of G. vaginalis such as those detected by the Affirmassay are frequently found in women with BV syndrome, they also occur ina subset of women without this condition, and without the ability tosimultaneously assess the presence of other potential BV markerorganisms, the specificity of the Affirm assay is compromised.

The use of a variety of DNA-based analysis tools, such as broad-rangeand quantitative PCR, has identified novel bacteria associated with BVwhile also providing more objective, quantitative measures of bacterialpresence. Use of DNA-based tools also has resulted in a greaterawareness of the complexity of microflora alterations underlying BV. Anumber of studies have been published describing the use of quantitativeor semi-quantitative PCR methodologies for diagnosing BV. The markerorganisms used in these studies differed, as did the cut-off valuesdescribed as optimal for differentiating abnormal samples from normalsamples. There is, as yet, no unified approach to using PCR technologyfor BV diagnosis.

In summary, currently available BV diagnostic methods suffer fromvarious disadvantages. The currently accepted diagnostic standards,namely the Amsel criteria and the Nugent Gram-stain score, rely heavilyon the proficiency of the individual clinician and/or laboratory, andare effectively impossible to standardize. Simple indirect laboratorytests such as the BV Blue test, are prone to problems in sensitivity(loss of enzyme activity) and specificity (inappropriate samplecollection) and are thus of limited value. The Affirm test relies ondirect detection of bacterial DNA and improved accessibility and iseasier to employ than the known approaches discussed above, but allowsfor only qualitative detection of a single organism (G. vaginalis), andthus lacks diagnostic accuracy.

What is needed is an improved diagnostic method for detecting BV inpatients. Such an improved method would be accurate, cost-effective toperform, clinically predictive and readily interpretable, whilesimultaneously being compatible with tests for alternate etiologies ofvaginitis (eg Candida spp. and T. vaginalis) and other STIs (such aschlamydia and gonorrhea). The improved BV diagnostic method would takeinto account more than one BV-associated organism, and at the same timewould be readily interpretable by a clinician, who would be able eitherto use the data from the improved test to diagnose BV in a patient, orcombine, according to an established and easy to perform procedure, theresults from the improved tests with other available diagnostic methodsin order to achieve diagnosis of BV in a patient with high level ofaccuracy.

Provided herein are improved methods useful for diagnosing bacterialvaginosis (BV). Generally, the methods for diagnosing BV describedherein involve determining an amount or concentration of more than oneBV-associated bacteria, or marker, in a vaginal sample, and determiningthe BV status of the patient from the amount of the BV-associatedbacteria present in the sample. Unlike some of the conventional methodsthat rely on the observation of a vaginal sample (in the form or amicroscope slide) by a trained person, such as a clinician, the methodsof the present invention use objective, quantifiable measures ofbacterial occurrence in samples, namely, the presence of specificbacterial molecules, which are referred to as molecular markers. Suchmarkers are detected according to established and reliable techniquesand procedures. Accordingly, the methods of the present invention areless dependent on the subjective acumen of the person performing themethod than methods involving microscopic examination.

The term “bacterial vaginosis,” abbreviated as “BV,” and similar termsused herein are to be understood in the broad sense as the alterationsof vaginal bacterial flora composition in a woman, as compared to abaseline, reference or “normal” vaginal bacterial flora composition. Inother words, the term “bacterial vaginosis” and related terms are notlimited to a specific vaginal bacterial flora composition or anyparticular symptoms observed in a particular woman or population ofwomen. While BV can manifest itself through a variety of symptoms, someof which are discussed elsewhere in this document, BV can also beasymptomatic. In certain situations, BV may be considered a medicalcondition or disease that requires treatment, while in other situationsBV may be viewed as a benign variation of the vaginal bacterial flora.Regardless of the specific definition of BV, or the baseline orreference bacterial flora used, BV diagnostic methods described hereinare generally probative for vaginal microflora alterations, and can beused to determine such alterations in both symptomatic and asymptomaticfemales.

Improved methods useful for diagnosing BV can be also referred to as BVdiagnostic methods, tests or assays. All these terms can be usedinterchangeably and fall within the scope of the present invention.“Diagnosis,” “diagnosing,” and related terms refer generally to aprocess or result of BV detection, identification or determination. Theterms diagnosis, detection, identification, determination, assaying,testing and related terms, when used in reference to BV or in thecontext of the methods of the present invention can denote showing,indicating, discovering or determining one or more of presence of BV,absence of BV, prevalence, progression, level or severity of BV, as wellas a probability of BV, present or future occurrence or exacerbation ofsymptoms of BV, consequences or complications of BV, or to efficacy of atreatments. The foregoing list is not intended to be exhaustive, andthese terms “diagnose,” “detect,” “indicate,” “identify,” “indicative,”“determine,” “assay,” “test” and similar terms can also refer to otherthings.

The molecular markers detected in the methods of the present inventionare exemplified by bacterial nucleic acids, such as DNA or RNA. Thenucleic acid markers are nucleic acid sequences specific to a particularcategory of BV-associated bacteria, such as a bacterial species or agenus. For example, the molecular markers used in some embodiments ofthe present invention are nucleic acid sequences specific to one or morethe following bacteria: Atopobium vaginae, Bacterial VaginosisAssociated Bacterium (such as BVAB-1, BVAB-2 or BVAB-3), Megasphaera-1,G. vaginalis, or Lactobacillus crispatus. However, the molecular markersof the present invention are not limited to the nucleic acid sequencesof the above-listed bacterial species. It is understood that othercurrently known bacteria can be used as BV markers in the embodiments ofthe present invention, and that newly recognized bacteria can becultured from the samples or detected in libraries of clones fromsubjects with BV and used as markers in the embodiments of the presentinvention. It is envisioned that the methods of the present inventioncan be modified to detect a variety of BV-associated bacteria, and themolecular markers used in a particular embodiment of the methods of thepresent invention would be modified accordingly.

The detection of nucleic acids employed in some embodiments of themethods described in this patent is less prone to environmentalinterferences and user errors, as compared to the so-called “indirect”assays of metabolic or enzymatic activity. Also, the nucleic acidmarkers employed in some of the embodiments of the methods of thepresent invention allow for specific detection of various bacterialspecies, unlike the non-specific enzymatic or metabolite markers thatcan be produced by several different bacteria. The nucleic acid markersused in the embodiments of the methods described herein, as well as theprobes for detection of the markers, can be selected or modified toallow for more or less specific detection of various bacterial groups.For example, some of the markers or the probes can be selected to detectwhole genera of bacteria, such as Lactobacillus, while the otherembodiments may employ markers or probes that detect specific bacterialspecies. Various markers and probes can be selected and modified inorder to choose a combination of markers and probes with an optimalpredictive value desired for a particular situation. Thus, the methodsof the present invention allow for increased assay flexibility in thetest design, and can be easily adapted for a particular patientsubgroup, purpose, or to account for new information on bacterialpopulations.

BV diagnostic methods according to the present invention and its variousembodiments use quantitative measures of bacterial occurrence in vaginalsamples. The term “occurrence,” when used in reference to the bacteriadetected according to the embodiments of the present invention is usedto denote incidence of the bacteria, as well as frequency of theirappearance, quantity, or distribution throughout different categoriesand subcategories. Combination of such information on the occurrence ofbacteria can be referred to as a “pattern.” The information onoccurrence of bacteria, or bacterial patterns, obtained from the samplesinvestigated in the course of performing the BV diagnostic methodsaccording to the present invention, can be compared or correlated withthe information on bacterial occurrence in other samples, or to theinformation obtained by other methods from the same samples. Suchinformation can be obtained prior to, concurrently with, or subsequentlyto the performance methods of the present invention. It is to beunderstood that any information used for comparison can be processed andstored, including processing and storage in computer form. Occurrence ofbacteria is used in some embodiments of the present invention as acharacteristic measured and evaluated as an indicator of BV. Some otherembodiments of the present invention use the information on theoccurrence of bacteria to identify the categories or combinations ofbacteria that can be used as markers of BV in a patient.

Detection of BV according to various embodiments of the methodsdisclosed herein can employ appropriate analytical methods, techniquesor procedures. In some embodiments of the detection methods,quantitative or semi-quantitative PCR is employed to detect bacterialmarkers. However, it is envisioned that other suitable analyticaltechniques can be employed in other embodiments, such as immunochemicaltechniques or mass-spectroscopy. In one embodiment, a multiplexedquantitative PCR assay is used to detect several molecular markers in asample simultaneously. The categories of bacteria quantitativelydetected by the improved methods can be bacterial species or genera.

The term “sample,” as used in this patent, refers to any sample suitablefor testing or assaying according to the methods of the presentinvention. One example of a sample can be referred to as a gynecologicalsample, such as a vaginal swab obtained according to the proceduresaccepted in the medical field. However, the term “sample” is not limitedto vaginal swabs, but can also be used to describe discharge or mucussamples, tissue sample or cell samples, obtained, processed, transportedand stored using various suitable procedures. For examples, the samplescan be stored in suitable storage or transportation devices,refrigerated, frozen, desiccated, diluted, mixed with various additives,or mounted on slides.

The BV-associated bacteria detected using the molecular markersdescribed herein are also referred to as “bacterial markers” and belongto a variety of bacterial genera and species. Some of the genera areLactobacillus, Atopobium, Gardnerella, Mobiluncus, Bacteroides,Leptotrichia, Sneathia, Porphyromonas, and Mycoplasma. Some of thebacterial species are Atopobium vaginae, BVAB-2, Megasphaera-1,Lactobacillus crispatus, and Gardnerella vaginalis. The terms “bacterialmarker” or “bacterial markers” are used herein to refer to one or morebacteria, or certain combinations of bacteria, whose occurrence can beused for assessment of BV status of a vaginal sample. Bacterial markersare selected for detection by the BV diagnostic methods of the presentinvention so as to provide a clinically meaningful assessment, based onthe results of detection, of the occurrence of BV in a woman from whomthe vaginal sample was obtained. The amount or presence of a bacterialmarker in a sample can be positively or negatively correlated with thepresence of BV in a patient from whom the sample was obtained.Accordingly, the marker can be referred to as a negative or a positivemarker.

Some of the bacterial markers utilized by the present invention arenormal inhabitants of a human body, and are often referred to as“commensal” bacteria, particularly when they are not associated with anypathological states or conditions. Some other bacteria can be describedas “pathological,” particularly if they are typically not found in humanbody, or found in low numbers, and their presence or increased numbersis associated with a pathological state. It is noted that the samebacterial species can be classified as both “commensal” or“pathological,” depending on the accepted classification system,pathology paradigm, bacterial numbers, and other factors. The presentinvention is therefore not limited to the using commensal, pathological,or any other category of bacterial markers.

The bacterial markers are selected for the embodiments of the presentinvention in order to provide improved diagnostic characteristics withrespect to determination of the BV status of a female patient. Theselection of the bacterial markers can be modified or adjusted toimprove or optimize diagnostic characteristics of the BV diagnosticmethods of the present invention in a patient population. Suchdiagnostic characteristics can be also referred to as “probative value.”Some criteria for assessment of probative value are predictive value,sensitivity, and specificity. The term “predictive value” is used hereinto denote a parameter that is used to characterize a correlation betweenthe presence of BV in a patient or a group of patient and the occurrenceof a particular bacterium or groups of bacteria. “Predictive value” canreflect positive correlation and be referred to as “positive predictivevalue,” or can reflect negative correlation and be referred to as“negative predictive value.” The terms “sensitivity” and “specificity”are used herein to refer to statistical measures of the performance ofdiagnostics tests. Sensitivity refers to a proportion of positiveresults which are correctly identified by a test. Specificity measures aproportion of the negative results that are correctly identified by atest. Examples of the calculations used to determine predictive value(positive and negative), specificity and specificity are describedelsewhere in this patent.

Diagnostic methods or tests according to some embodiments of the presentinvention advantageously use at least one bacterial marker that has highspecificity, and at least one bacterial marker that has highsensitivity. It was discovered that employing a combination of at leasttwo markers with these characteristics achieves improved probative valuefor a BV diagnostic test. The term “high specificity” refers tospecificity that is equal or over 80%, 81%, 82%, 83%, 84%, 85%, 86%,87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%. Inone example, high specificity refers to specificity of approximatelyover 90%. In another example, high specificity refers to specificity ofapproximately over 95%. The term “high sensitivity” refers tosensitivity that is equal or over 80%, 81%, 82%, 83%, 84%, 85%, 86%,87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%. Inone example, high sensitivity refers to sensitivity of approximatelyover 90%. In another example, high sensitivity refers to sensitivity ofapproximately over 95%. The selection of the bacterial markers used inthe improved BV diagnostic methods of the present invention can dependon a number of factors, such as the patient characteristics or thehealth risks associated with particular markers or patientcharacteristics. The diagnostic tests according to some embodiments ofthe present invention can advantageously use at least one bacterialmarker that has high specificity but low sensitivity, and at least onebacterial marker that has high sensitivity but low specificity. The term“low sensitivity” refers to sensitivity that is equal or less than 75%,76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%,90%, 91%, 92%, 93%, 94% or 95%. In one example, low sensitivity refersto specificity of approximately less than 78%. In another example, lowsensitivity refers to sensitivity of approximately less than 89%. Theterm “low specificity” refers to specificity that is equal or less than75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%,89%, 90%, 91%, 92%, 93%, 94% or 95%. In one example, low specificityrefers to specificity of approximately less than 78%. In anotherexample, low specificity refers to specificity of approximately lessthan 89%. The positive predictive value for the BV diagnostic methodsaccording to the embodiments of the present invention can range fromapproximately 50% to approximately 99%. For example, positive predictivevalue can be approximately 55%, 58%, 76%, 85% or 90%. Negativepredictive value for the BV diagnostic methods according to theembodiments of the present invention can range from approximately 95% toapproximately 99.5%. For example, negative predictive value can beapproximately 98%, 98.5%, 99% or 99.5%. The methods according toembodiments of the present invention can have increased positivepredictive value, as compared to previously known tests. For example,positive predictive value can be approximately 20-40%, 22-33% higher, or25-30% higher than the positive predictive value for a conventional testin a given population.

Markers selected for BV diagnosis may be different for different patientpopulations. For example, different bacterial markers may be selectedfor populations with different prevalence of BV. In other examples,different bacterial markers may be selected for different ethnic or agegroups, or have different baseline or reference vaginal bacterialpopulations. The selection of bacterial markers may be changed based onthe distribution of various markers in a particular patient populationin both a baseline (non-BV) state and BV states of various severities.In another example, different bacterial markers may be selected fordetecting BV in pregnant women than for non-pregnant women. In one moreexample, different bacterial markers may be used to detect BV inHIV-positive and HIV negative patients, depending on the health risksassociated with different bacteria for each of the groups.

In one embodiment of the BV diagnostic method described in this patent,a combination of A. vaginae, BVAB-2, G. vaginalis, Megasphaera-1 and L.crispatus is used to delineate BV. In another embodiment, a combinationof A. vaginae, BVAB-2, G. vaginalis, Megasphaera-1 is used as a markerfor BV. In another embodiment, L. crispatus is included in a group ofbacterial markers as a negative predictor for BV. The number ofbacterial markers used in various embodiments of the present inventioncan be two, three, four, five, six, seven, eight or higher. The methodsand procedures for selecting the bacterial markers to be used in the BVdiagnostic methods are included within the scope of the presentinvention, as well as the combinations of bacterial markers describedherein, which are used for diagnosing, predicting or assessing BV in apatient.

The improved BV diagnostic methods characterize the bacterial markersdetected in a sample using a scoring method, which is then translatedinto a clinical interpretation of a BV status of the sample. The scoringmethod used in the improved BV diagnostic methods assigns scores toindividual bacterial markers based on their levels, determined as amountor concentration of a bacterial marker detected in a sample, andgenerates a composite score from the individual bacterial marker scores.The scoring method is included within the scope of the presentinvention. In order to develop a scoring method for various bacterialmarkers, cut-off values for bacterial marker levels are determined. Whena diagnostic method is performed, the cut-off values are used toclassify the samples into different categories with respect to thelevels of a bacterial marker in each category (for example, low, mediumor high). In order to determine the cut-off values, levels of abacterial marker are determined by appropriate analytical procedures inthe samples obtained from a patient population. The statisticaldistribution of the levels of the marker in a given sample set iscalculated or otherwise evaluated, quantitatively or qualitatively. Forexample, a fraction of the samples associated with a particular range ofthe levels of the marker is calculated. Based on the evaluation, cut-offvalues are determined. The scores to be assigned to each of the rangesare also determined. Samples are then assigned, categorized orclassified into a category based the amount or levels of the markerdetected in the samples. Based on the categorization, concentrations foreach of the markers utilized in a particular embodiment of the test areconverted into a score characteristic of the concentration or levels ofthe marker. The individual scores are combined into a composite score,which is used in clinical interpretation of the test results. FIG. 1provides a schematic illustration on the distribution of several markersin a particular patient population as well as determination of thecut-off values for each marker. The scoring method according to thepresent invention can be flexibly adjusted to reflect distribution ofvarious bacterial markers in various patient populations so as toachieve improved probative value and clinically meaningful diagnosticdata for different sample sets, patient populations and bacterialmarkers.

BV diagnostic methods described herein are accurate, cost-effective,clinically predictive and readily interpretable. They are compatiblewith other tests for urogenital conditions and/or sexually transmitteddiseases (STIs), such as candidiasis, trichomoniasis, chlamydia,gonorrhea and others. The BV diagnostic methods of the present inventionare at least as sensitive and specific as the conventional testscurrently employed for BV diagnosis, such as Nugent Gram stain scoringapproach and Amsel interpretation, when the conventional tests areperformed by skilled practitioners. They are least as sensitive butsignificantly more specific than tests using single molecular markers,such as BD Affirm Assay.

The BV diagnostic methods described herein utilize a relatively simpleand robust design and scoring method that enables accuratedifferentiation of BV positive and negative samples to be performed in astandardized and cost-effective manner. BV diagnostic methods and samplescoring methods described herein provide improved clinical testing andmanagement options for the common and problematic syndrome of bacterialvaginosis.

EXAMPLES

Embodiments of the present invention are illustrated by the followingexamples, which are not to be construed in any way as imposinglimitations upon the scope thereof. On the contrary, it is to be clearlyunderstood that resort may be had to various other embodiments,modifications, and equivalents thereof, which, after reading thedescription herein, may suggest themselves to those skilled in the artwithout departing from the spirit of the invention. During the studiesdescribed in the following examples, conventional procedures werefollowed, unless otherwise stated. Some of the procedures are describedbelow for illustrative purpose.

Example 1 Clinical Evaluation

Evaluation of 396 patients was conducted with the goal of developing aclinically validated test for BV based on nucleic acid amplification,such as qPCR, and quantification of key indicator organisms. Theevaluated patient population consisted of adult females at least 18years of age. Multiple vaginal swabs were collected from each evaluatedpatient and tested according to standard BV diagnosis procedures (termed“gold standard”), namely, Nugent Gram-stain scoring system and Amselcriteria. Additional, vaginal swabs were tested by the Affirm test andqPCR assays for several bacterial markers. The information fromdifferent qPCR assays was used to determine BV status of each sample,and the results were statistically analyzed and compared with theresults of Nugent Gram-stain scoring system, Amsel criteria and Affirmtest.

Example 2 Patient Population

A total of 402 women presenting for clinical evaluation at either theSexually Transmitted Diseases Clinic, Jefferson County Department ofPublic Health (JCDH), Birmingham, Ala. (299 patients), or the PersonalHealth Clinic (PHC), University of Alabama-Birmingham, Birmingham, Ala.(103 patients) between April and October, 2011 were enrolled in thestudy. All enrolled patients were over 18 years of age, and did notreceive antibiotics or use vaginal medications, including antifungalmedications, for at least 14 days prior to enrollment. Evaluations couldnot be completed on 6 enrollees, thus, the results from 396 patientswere available for the clinical evaluation described in the earlierexample.

Example 3 Sample Collection

Informed consent was obtained from all the patients. A series of vaginalsamples was collected from each patient in order to conductcomprehensive evaluation for markers of vaginitis, including bacterialmarkers, Candida spp. and Trichomonas vaginalis, and testing forChlamydia trachomatis and Neisseria gonorrhoeae. The sample seriescontained the samples described below. A standard vaginal swab wascollected and used to prepare a smear for Gram staining procedure on amicroscopy slide. The microscope slide was stained according to Gramstaining procedure and assessed in the field by a qualified clinicianaccording to the Nugent scoring system. The same vaginal swab that wasused for Gram staining, was then placed in Affirm™ VPIII transportsystem (Becton-Dickinson, Sparks, Md.) with dropper vial additive. Thesecond vaginal swab was collected and placed into ESwab™ (CopanDiagnostics Inc., Murrieta, Calif.) transport system for culture andconfirmatory Gram stain evaluation. Two additional swabs were collectedusing the APTIMA™ vaginal swab collection device (GenProbe™ Inc., SanDiego, Calif.) for nucleic-acid amplification testing.

Example 4 Sample Assessment According to Conventional Gold StandardMethods

For each evaluated patient, BV status was ascertained by clinicalassessment using the gold standard: the Amsel criteria assessment of avaginal secretion sample and Nugent scoring performed on a Gram-staineda vaginal swab sample.

For Amsel criteria assessment, vaginal secretions were collected fromeach patient and evaluated at the point of collection according to theAmsel criteria. The following standard Amsel criteria were assessed andrecorded for each patient: presence of thin, whitish, homogenous vaginaldischarge; amine (fishy) odor on the addition of KOH to the wet mountedvaginal discharge material, the presence of clue cells upon microscopicexamination of vaginal discharge samples; and a pH value of greater than4.5 for the vagina discharge.

Vaginal samples were also evaluated according to Nugent Gram-stainscoring system. Quantitative Gram-staining for each sample was performedaccording to standard procedures. In brief, a standard vaginal swab wasrolled across a glass microscope slide, air dried, and then fixed inmethanol prior to Gram staining. Gram-staining was performed.Gram-stained slides were then examined for specific bacterialmorphologies, and Nugent scores (NS: range 0-10) generated. An NS of 0-3was interpreted as normal or negative for BV, a score of 7-10 wasinterpreted as abnormal or positive for BV, and a score of 4-6 wasinterpreted as intermediate for BV.

In order to definitively classify samples as positive or negative forBV, the samples with intermediate NS that met the Amsel criteria for BVwere classified as BV positive, and the samples with intermediate NSthat failed to meet the Amsel criteria for BV were classified as BVnegative.

Example 5 Sample Characterization Results Based on the Gold Standard BVDiagnostic Methods

In the first phase of the study, 169 samples (“first sample group”) werecharacterized according to the conventional gold standard methods,namely, Amsel criteria assessment and Nugent Gram-stain scoring. Of the169 samples comprising the first sample group, 108 (63.9%) weredetermined to be BV positive and 61 (36.1%) were determined to benegative for BV according to the gold standard. Of the BV positivesamples, 96 (88.1%) had NS of 7-10, with 12 samples having NS of 4-6 andpositive Amsel results. Of the BV negative samples, 47 (77.0%) had NS of0-3, with the remaining 14 samples being Amsel negative and NSintermediate. 168/169 (99.4%) of samples in this phase of the study werecollected from patients attending the JCDH clinic. An additional 227samples were subsequently collected (“second sample group”). One hundredand thirty one (57.7%) of these samples were obtained from patientsattending JCDH, and 96 (42.3%) from patients attending PHC. Among thesecond sample group, 110 (48.5%) were positive and 107 (51.5%) negativefor BV. Unambiguous NS were obtained for 200/227 (88.1%) of the secondgroup samples, and of the 27 samples with intermediate NS, 8 wereresolved as positive and 19 as negative using Amsel criteria. Theoverall prevalence of BV in the study population was, therefore, 55.1%(218/396) with an NS intermediate rate of 13.6% (54/396). Of the 54 NSintermediate samples, 21 (38.9%) resolved as positive for BV using theAmsel criteria.

Example 6 Nucleic Acid Isolation

Nucleic-acid was extracted from vaginal swab suspensions prepared andstored in APTIMA™ collection system using the MagNAPure LC™ TotalNucleic Acid Isolation Kit on MagNAPure™ LC Instruments (Roche AppliedScience, Indianapolis, Ind.) according to the manufacturer'sinstructions. Prior to extraction, DNA Sample Processing Reagent(DNA-SPR; EraGen Biosciences, Madison, Wis.; 5 μl) was added to eachspecimen. DNA-SPR contains a proprietary, extractable, DNA target thatis used as an internal control in PCR assays to monitor recovery ofnucleic-acid and elimination of PCR inhibitors through samplepreparation. Nucleic acid was eluted in a final volume of 50 μl andeither analyzed immediately or stored at a temperature of less than −20°C.

Example 7 Quantitative PCR Assays

For quantitative PCR (qPCR) testing of the samples for the presence ofA. vaginae, BVAB-2, Megasphaera-1, G. vaginalis and L. crispatus, primerdesigns were developed for each of the organisms based on in silicoanalysis of published 16S rRNA gene sequences and are shown in Table 1.The primers were screened for multiplex qPCR compatibility and lack ofcross-reactivity. Assays were designed for use the primer-basedMultiCode®-RTx system (EraGen Biosciences, Madison, Wis.) for real-timeproduct detection. Generally, the MultiCode®-RTx system exploits thephysico-chemical properties of two unique synthetic nucleotide bases andallows for specific amplification of PCR products to be monitored asconcentration-dependent decreases in fluorescence, with confirmation ofamplification of the desired product accomplished post-amplification viadetermination of peak melting temperatures (T_(m)) of amplifiedproducts.

One member of each primer pair used in the qPCR assay for multiplemarkers contained a 2′-deoxy-5-methyl-isocytidine (iC) base coupled to afluorescein moiety immediately proximal to the 5′-terminus of themolecule. For quantitative measurement of the respective analytes,synthetic oligonucleotide Ultramers™ (Integrated DNA Technologies Inc.,Coralville, Iowa) were used to construct calibrating material. EachUltramer contained the target sequence of one of the intended analytes,and quantitative analytical data provided by the manufacturer was usedas the basis for value assignment (in DNA copies) of these materials.All qPCR assay runs included a set of 3 ultrameric calibrators, andinterpolation of crossing threshold (Ct) values generated during PCRamplification of vaginal samples into calibration curves enabled thederivation of DNA concentrations per mL of sample for each analyte. Atotal of 5 μL of extracted nucleic-acid (corresponding to 20 μL oforiginal vaginal sample), was utilized for qPCR amplification reactions,and the dynamic range of all qPCR assays was established at 1×10³-1×10⁸copies/mL. Amplification reactions were performed on RotorGene™ Qinstruments (QiaGen Inc., Chatsworth, Calif.) using the followingconditions: initial denaturation for 2 min at 95° C., 50 cycles ofamplification (95° C.×5 sec, 58° C.×10 sec, 72° C.×20 sec (fluorescencecollected during this step); with post-amplification melt analysis (60°C. to 95° C. ramp, 1.0° C. per second).

Example 8 Multiplexed qPCR Assay

The BV PCR design consisted of a pair of multiplexed PCR reactions. BV-1contained the A. vaginae primer pair (5-carboxyfluorescein (FAM)labeled) and an internal control primer pair (6-hexachlorofluorescein(HEX labeled). BV-2 contained the BVAB-2 primer pair (FAM labeled) andthe Megasphaera-1 primer-pair (HEX labeled). Each BV PCR run contained 2ultrameric calibrators for the Av reaction (set at 7.0 log₁₀ copies/mLfor Cal-1 and 5.5 log₁₀ copies/mL for Cal-2), 2 ultrameric calibratorsfor the BVAB-2 reaction (set at 6.0 log₁₀ copies/mL for Cal-1 and 4.5log₁₀ copies/mL for Cal-2), and a single ultrameric calibrator forMegasphaera-1 set at 6.0 log₁₀ copies/mL. Each run also containedappropriate negative and positive extraction controls to monitor assayperformance.

Example 9 qPCR Testing Results Using Single Known BV Bacterial Markers

Five organisms were separately detected by qPCR in the 169 samples ofthe first sample group: A. vaginae, BVAB-2, G. vaginalis. Megasphaera-1and L. crispatus. Comparison of qPCR testing results obtained for eachseparate marker and gold standard results is illustrated in Table 2. Allfour of the qPCR-detected organisms that are known to be positive BVmarkers were frequently present in samples designated as BV positive.Using an assay cut-off value of 1×10³ copies/mL, 98.1% (106/108) BVpositive samples were positive for G. vaginalis, 98.2% (106/108) of theBV positive samples were positive for A. vaginae, 89.8% (97/108) of theBV positive samples were positive for BVAB-2, and 87.0% (94/108) of theBV positive samples were positive for Megasphaera-1.

The frequency with which these organisms were found in BV negativesamples were appreciably different among the organisms. 60.7% (37/61) ofBV negative samples were positive for G. vaginalis, 52.5% (32/61)positive for A. vaginae, 18.0% (11/61) for BVAB-2, and 16.4% (10/61) forMegasphaera-1.

TABLE 1Primer sequences used to detect indicated 16s rRNA regions of target organismsGenBank 5′- Accession Target Primer ID Sequence (5′→3′) Location NumberA. vaginae AvFP-BV1 FAM-isodC-CCC TGG TAG TCC TAG CT^(a)  746 AJ585206AvRP-BV1 (SEQ ID NO: 1) CGG CAC GGA AAG TAT AAT CT  808 (SEQ ID NO: 2)BVAB-2 BvabFP-BV2 FAM-isodC-CGT GTA GGC GGC TAG ATA  199 GQ900639BvabFP-BV2 AGT G (SEQ ID NO: 3) TCC AGC ACT CAA GCT AAA CAG TTT GT  283(SEQ ID NO: 4) G. vaginalis Gv-16s-F1FAM-isodC-GTG ACA TGG TGC TAA TCC CT 1226 HQ114564 Gv-16s-F2(SEQ ID NO: 5) GCT GCC CAC TTT CAT GAC TT 1388 (SEQ ID NO: 6)Megasphaera-1 MegaFP-BV2 GCT CTG TTA TAC GGG ACG AAA AAG  419 AB279971MegaRP-BV2 (SEQ ID NO: 7 ) FAM-isodC-CGG ACG GAT ACT GTT GGC  462ATC (SEQ ID NO: 8) L. crispatus Lc-16s-F1CAG GTC TTG ACA TCT AGT GCC ATT T  969 HQ716720 Lc-16s-F2 (SEQ ID NO: 9)FAM-isodC-CAT GCA CCA CCT GTC TTA G 1041 (SEQ ID NO: 10) ^(a)FAM:5-carboxyfluorescein is used as the reporter dye and is coupled to theinitial 5′-nucleotide in the primer. isodC:2′-deoxy-5-methyl-isocytidine is the initial nucleotide at the 5′-end ofthe fluorescently labeled primer.

Analysis of the distribution of quantitative values also demonstratedappreciable differences in organism concentrations in BV positive andnegative sample populations, as illustrated in Table 2. The medianconcentration observed in BV positive and negative populations differedby 3.5 log¹⁰ copies/mL for G. vaginalis, 3.8 log¹⁰ copies/mL for A.vaginae, >3.1 log¹⁰ copies/mL for BVAB-2, and >3.9 log¹⁰ copies/mL forMegasphaera-1.

L. crispatus was evaluated as a negative BV marker and was found at anunexpectedly low rate in the study population with only 37/169 (21.9%)samples having >1×103 copies/mL of this organism. The frequency ofdetection of L. crispatus in BV positive samples was significantly lowerthan that observed in BV negative samples (10.2% v 42.6%; p<0.01),however, a majority (57.4%) of BV negative samples in this populationlacked detectable levels of this organism.

Analysis of data generated from the single marker qPCR testsdemonstrated that the utility of A. vaginae and G. vaginalis, highlysensitive markers for BV, was limited by their low specificity, or highfrequency with which they were identified in samples from patients notclassified as BV positive. BVAB-2 and Megasphaera-1 were somewhat morespecific indicators of BV positivity than either G. vaginalis or A.vaginae, but at least one of these organisms was present in asignificant subset of BV negative study subjects.

TABLE 2 Results of quantitative PCR measurements of marker organisms invaginal samples identified as positive or negative for BV according togold standard. PCR qPCR Values Results^(b) (log₁₀ copies/mL) BV Nega-Posi- 25^(th) 50^(th) 75^(th) Organism Status^(a) tive tive Pct Pct PctA. vaginae Negative 29 32 <3.00 3.11 4.98 Positive 2 106 6.52 6.90 7.32BVAB-2 Negative 50 11 <3.00 <3.00 <3.00 Positive 11 97 5.38 6.04 6.64 G.vaginalis Negative 24 37 <3.00 3.48 5.31 Positive 2 106 6.61 6.99 7.53Megasphaera-1 Negative 51 10 <3.00 <3.00 <3.00 Positive 14 94 6.18 6.897.18 L. crispatus Negative 35 26 <3.00 <3.00 7.55 Positive 97 11 <3.00<3.00 <3.00 ^(a)BV status was defined based on a combination of NugentGram-stain score (NS) and Amsel's criteria. BV positive samples werethose with NS value of 7-10 and samples with NS values of 4-6 that metAmsel's criteria. ^(b)Samples that generating qPCR values below thelower limit of quantitation of the respective assays (1000 copies/mL)were considered negative. Pct is an abbreviation for “percentile.”

Example 10 Statistical Analysis of qPCR Data for Known Marker Organisms

Statistical analysis of qPCR data obtained for known marker organismsindicated that no single marker organism reliably differentiated betweenBV positive and BV negative samples. G. vaginalis and A. vaginae eachdemonstrated high sensitivity, but limited concentration discriminationobserved for each of these organisms between the 4^(th) quartile of thenegative population and the 1^(st) quartile of the positive samplepopulation compromised specificity. BVAB-2 and Megasphaera-1, bycontrast, demonstrated lower overall sensitivity, but greaterconcentration discrimination between positive and negative populations.

Logistic regression analysis (MedCalc Software Suite) was performed onall marker combinations using the results obtained for the 169 samplesof the first sample group (illustrated in Table 3). BV status of thepatients, based on NS plus Amsel criteria was used as the dependentvariable (negative=0, positive=1), and the qPCR results of thecombinations of marker organisms were used as the independent variable.The results of this analysis demonstrated that certain combinations ofthree marker organisms, namely, A. vaginae/BVAB-2/Megasphaera-1 or G.vaginalis/BVAB-2/Megasphaera-1, offered advantageous combination ofsensitivity and specificity, with both parameters exceeding 90% forthese combinations (illustrated in Table 3).

None of the tested combination of two markers reported in this examplegenerated both sensitivity and specificity parameters of >90% in thedevelopment phase sample cohort. This finding unexpectedly contradictsthe earlier reports by others on a reasonable specificity for BV using aqualitative combination of A. vaginae and G. vaginalis, or thatqualitative detection of either BVAB-2 or Megasphaera-1 was highlysensitive and specific when compared against either NS or Amselcriteria.

The experimental data summarized in this example indicated that acombination of BVAB-2 and Megasphaera-1 also lacked a high level ofspecificity, even if only samples with NS values of ≥7 are considered aspositive and intermediate NS samples excluded from analysis. Of the 47samples in the first sample group with NS of ≤3, 9 (19.1%) had positiveresults for either BVAB-2 (2 samples), Megasphaera-1 (4 samples), orboth organisms (3 samples), using a threshold for positivity of 1×10³copies/mL. Performance of this combination using only the Amsel criteriafor BV designation was even less probative, with either Megasphaera-1 orBVAB-2 DNA detected in 26/72 (36.1%) Amsel negative samples in the firstsample group. These results were unexpected in view of the earlierstudies by others using comparable value assessment (the medianquantitative values for each of the markers in BV positive patients inthe earlier studies were only 0.5 log₁₀ DNA copies per sample higherthan those described here).

TABLE 3 Results of logistic regression analysis of qPCR results forvarious marker organism combinations PCR Statistical Number Category^(c)Metrics of BV Nega- Posi- Sensi- Speci- Markers Organisms^(a) Status^(b)tive tive tivity ficity 2 Av/BVAB-2 Negative 50 11 95.4% 82.0% Positive5 103 Av/Gv Negative 47 14 95.4% 77.0% Positive 5 103 Av/Mega-1 Negative53 8 94.4% 86.9% Positive 6 102 BVAB-2/Gv Negative 50 11 96.3% 82.0%Positive 4 104 BVAB-2/ Negative 54 7 92.7% 88.5% Mega-1 Positive 7 101Gv/Mega-1 Positive 53 8 93.5% 86.9% Negative 7 101 3 Av/BVAB-2/ Negative51 10 95.4% 83.6% Gv Positive 5 103 Av/BVAB-2/ Negative 55 6 95.4% 90.2%Mega-1 Positive 5 103 Av/Gv/Mega-1 Negative 53 8 94.4% 86.9% Positive 6102 BVAB-2/Gv/ Negative 55 6 93.5% 90.0% Mega-1 Positive 7 101 4Av/BVAB-2/ Negative 52 9 95.4% 85.2% Gv/Mega-1 Positive 5 103 ^(a)Av =Atopobium vaginae, Gv = Gardnerella vaginalis, Mega-1 = Megasphaera-1.^(b)BV status was defined based on a combination of Nugent Gram-stainscore (NS) and Amsel criteria. BV positive samples were those with NSvalue of 7-10 and samples with NS values of 4-6 that met Amsel criteria.^(c)Categorized using logistic regression analysis, with BV status asthe dependent variable (negative = 0; positive = 1), and qPCR results onthe 169 samples of the first sample group for the different markercombinations as the independent variable.

Yet another earlier report by others stated that a combination of A.vaginae and G. vaginalis analyzed quantitatively may be used toaccurately differentiate BV positive from negative samples, usingthreshold concentrations of 10⁸ copies/mL and 10⁹ copies/mL,respectively. Logistic regression analysis of the first sample groupdescribed in this example unexpectedly demonstrated that quantitativeanalysis of these 2 markers, in combination, was not able to reliablydifferentiate BV positive from BV negative samples.

Example 11 Three-Marker Test Performance Using Individual qPCR Detectionfor Each Marker Organism

A test employing qPCR testing of three bacterial marker organisms(“three-marker qPCR test”) was developed. In this example, individualqPCR analysis of vaginal samples for each organism was employed todetect the concentrations of each of A. vaginae, BVAB-2 andMegasphaera-1 bacteria.

Analytical cut-off values were selected to categorize the samples, asillustrated by FIG. 1. Frequency distributions of the values generatedby qPCR for the three selected marker organisms (A. vaginae, BVAB-2, andMegasphaera-1) were compared against designation of samples by NS.Breakpoint values were selected that best differentiated samplepopulations into ‘high’ medium′ and ‘low’ categories, correlating with‘high’, ‘intermediate’ and ‘low’ NS. For Megasphaera-1 (see FIG. 1,panel C), an intermediate category was not created because of the sharpbreakpoint associated with the transition from low to high qPCR values.

The individual marker organisms were scored according to the criteriaset forth in Table 4. The total (or composite) test score was calculatedas the sum of the individual scores, as illustrated in FIG. 2. The sumof each organism's score equals the total score. As discussed earlier,samples with a total score of 0-1 were considered negative for BV,samples with a score of 3-6 were considered positive for BV, and sampleswith a score of 2 were considered indeterminate for BV. The total scoreinterpretation is schematically illustrated in Table 5. The compositescores were compared to the previously determined BV designations of thesamples, as illustrated in Table 6. The interpretive assignment ofresults and their comparison with the gold-standard results obtained forthe same sample group is shown in Table 7. The composite scoredemonstrated good correlation with the BV designation by NS and Amselfor a majority of the samples. Composite cores of 3-6 were highlycorrelated with positive samples, with 96.1% (98/102) of samplesyielding these scores being BV positive. Similarly, a score of 0 washighly correlated with negative samples, with 93.9% (46/49) of samplesyielding this score being BV negative.

The remaining 18 samples (10.7%; 11 BV negative, 7 BV positive) yieldedcomposite scores of 1-2. Of the 10 samples with a composite score of 1;2 had NS of ≤3, 6 had NS scores of 4-6, and 2 had NS of ≥7. Of the 8samples with a composite score of 2; 2 had NS of ≤3, 3 had NS scores of4-6, and 2 had NS of ≥7. The samples with composite scores of 2 weredesignated as ‘indeterminate’ for the purpose of BV diagnosis. It wasdetermined that since the composite score of 2 required the presence ofany of the 3 marker organisms at high concentration, or at least 2 ofthem (A. vaginae and BVAB-1) at moderate concentrations, this score isindicative of deviation from normal vaginal flora, however, only asubset of the samples could be classified as BV using conventional testmethods. Samples generating a composite score of 1 were designated asBV-negative. Upon excluding samples generating a score of 2 from thefinal analysis, the predicted sensitivity and specificity of the BV PCRconstruct on the remaining 161 samples were 93.3% (98/105) and 92.9%(52/56), respectively, with an indeterminate rate of 4.7% (8/169).

The experimental results reported in this example demonstrated thatinclusion of markers with high degree of specificity, for example BVAB-2and Megasphaera-1, as well as markers with a high degree of sensitivity,is advantageous in order to produce a qPCR test for BV having improvedpositive predictive value or values. Three-marker tests using qPCR assayfor A. vaginae, BVAB-2, and Megasphaera-1 provided an advantageouscombination of sensitivity and specificity, achieving 93.5% correlation(158/169) with the combined NS and Amsel gold standard.

Example 12 qPCR Sample Characterization and Scoring

Upon completion of a qPCR assay, results were exported into an MS Excelworksheet for scoring according to the scheme shown in Table 4.Composite scores (sum of 3 individual analyte scores) were thencompiled, and the final interpretation generated as follows: BV Negative(scores of 0-1), BV Indeterminate (score of 2), BV Positive (scores of3-6), as illustrated in Table 5.

TABLE 4 Scoring system used to categorize the samples analyzed by qPCRassay Organism Organism Concentration (log₁₀ DNA copies/mL) Atopobiumvaginae ≤5.5 5.5-7.0 >7.0 BVAB-2 ≤4.5 4.5-6.0 >6.0 Megasphaera-1 ≤6.0n/a >6.0 Score Low = Moderate = High = Score of 2 Score of 0 Score of 1

TABLE 5 Total score interpretation Total Score Interpretation 3-6Positive - indicative of bacterial vaginosis 0-1 Negative - notindicative of bacterial vaginosis 2 Indeterminate - unable to determineBV status. Additional clinical laboratory data should be evaluated toestablish a diagnosis.

Certain characteristics of qPCR testing (qPCR assay in combination withscoring and score interpretation) were determined as follows:

positive predictive value(PPV)=sensitivity/(sensitivity+(1−prevalence)(1−specificity))

negative predictive value(NPV)=((1−prevalence)specificity)/((1−prevalence)+prevalence((1−sensitivity))

sensitivity=samples determined as positive by qPCR testing/samplesdetermined as positive by the gold standard

specificity=samples negative by qPCR testing/samples negative by thegold standard

Example 13 Three-Marker Test Performance Using Multiplexed qPCR AssayDetection

Performance of the three marker qPCR test was tested using a multiplexedqPCR assay to analyze samples for the presence of the three bacterialmarkers: A. vaginae, BVAB-2 and Megasphaera-1 bacteria. Incorporation ofnucleic-acid calibrators in each qPCR run, at the concentrationsdetermined by qPCR analysis to be most probative in differentiatingpopulations of samples, allowed for categorization of samples withoutthe need for fully quantitative PCR analysis. The samples of the firstsample-group were analyzed with the three-marker test using multiplexedPCR, and the results of this BV diagnostic determination are shown inTable 6. The interpretive assignment of results and their comparisonwith the gold-standard results obtained for the same sample group isshown in Table 7. These results were highly congruent with thoseobtained by using individual qPCR assays for each marker with only 5 of169 samples (2.9%) generating categorically different results. Thesechanges resulted in one additional BV positive sample being classifiedas positive by BV PCR, one additional BV negative sample beingclassified as negative by BV PCR, two BV negative samples moving from anindeterminate to a negative PCR score, and one BV positive sample movingfrom a positive to an indeterminate PCR score. Overall, therefore,162/169 (95.9%) of the samples generated interpretable composite PCRscores in the multiplexed qPCR three-marker test, with the sensitivityof the assay being 94.2% (98/104) and the specificity 94.8% (55/58).

The additional 227 samples belonging to the second sample group werealso evaluated by the multiplexed qPCR three-marker test. A substantialminority of the samples of the second sample group were collected at thelower BV prevalence PHC location, thus the overall prevalence of BV inthe second sample group was 48.5% as compared to the 64.5% BV prevalencein the first sample group. The score assignments for the combined firstand second sample groups generated by multiplexed qPCR three-marker test(396 samples) are shown in Table 6, and the interpretive results andcomparison to the gold-standard results for the second sample group andthe combined sample group is shown in Table 7.

Results obtained for the second sample group were generally comparableto those obtained on the first sample group, thus supporting thevalidity of the scoring system created based on the individual qPCRtesting. Of the 227 samples in the second sample group, 14 (6.2%)yielded a composite score of 2 and were thus deemed indeterminate forBV, of which 9 were BV negative samples and 5 BV positive samples. Inthe total population tested, 21 samples generated a BV PCR score of 2, 9(42.9%) of these were BV positive samples and 12 (57.1%) were BVnegative samples, supporting the use of ‘indeterminate’ as a categoricaldesignation for specimens generating this composite PCR score. Of the213 samples that generated an evaluable PCR score in the second samplegroup, 104 of 105 (99.0%) BV positive samples generated a positive PCRscore, and 98 of 108 (90.7%) BV negative samples generated a negativescore. Of the 17 samples in the second sample group that generated acomposite PCR score of 1, only 1 was a BV positive sample, confirmingthe appropriateness of categorizing samples with this score as BVnegative.

Analysis of the combined sample group (396 samples) demonstrated thatthe three-marker qPCR test using multiplexed qPCR had a sensitivity of96.7% (202/209), a specificity of 92.2% (153/166), a positive predictivevalue of 94.0% and a negative predictive value of 95.6%, with anindeterminate rate of 5.3% (21/396).

Using a combination of three marker organisms, A. vaginae, BVAB-2, andMegasphaera-1, in an assay format that segregated samples intomarker-specific populations (high, medium, low) based on theirrelationship to breakpoint DNA concentrations, enabled 94.7% (375/396)of the samples of the combined sample group to be categorized withrespect to the presence or absence of BV with an overall accuracy of94.7% (355/396). Analysis of the 20 samples generating discordantresults between BV status determined by qPCR test and BV status by NSand Amsel criteria revealed the challenge of attempting to correlatemolecular data for this condition with conventional techniques.

Analysis of the samples generating discordant results between thethree-marker qPCR test and BV status by NS and Amsel criteria revealedthat the three-marker qPCR test detected patient-specific changes inmicroflora that may not be detected by conventional clinical methods. Ofthe 13 BV negative samples that were positive by BV PCR, only 3 had NSof ≤3, and of the 7 BV positive samples that were negative by BV PCRonly 1 had an NS of ≥7, and this patient was negative by Amsel criteria.Thus only 4/20 (20%) of the results discordant between the three markerqPCR test determination and gold-standard test determination could beunambiguously categorized by NS, the remainder were NS intermediatesamples, a cohort likely to have significant, patient-specific,variation in the extent of correlation of symptoms with specific changesin microflora.

TABLE 6 Distribution of composite PCR scores by BV status Composite PCRScore Sample Set Assay^(a) BV Status 0 1 2 3 4 5 6 First Sample qPCRNegative 46 6 5 1 3 0 0 Group (61) (n = 169) Positive 3 4 3 11 29 32 26individual (108) qPCR assay BV-PCR Negative 46 9 3 2 1 0 0 (61) Positive3 3 4 17 25 29 27 (108) First Sample BV-PCR Negative 82 16 9 3 6 1 0Group (117) (n = 169) Positive 0 1 5 8 29 25 42 multiplexed (110) qPCRassay) Combined BV-PCR Negative 128 25 12 5 7 1 0 Sample (178) GroupPositive 3 4 9 25 54 54 69 (n = 396) (218) ^(a)qPCR: Individualquantitative determinations of analyte concentrations. Scores determinedby comparison of qPCR values with breakpoint concentrations establishedfrom frequency distributions of development phase sample cohort; BV-PCR:Semi-quantitative assay using internal calibrators to assign individualanalyte scores.

TABLE 7 Correlation of interpretive results generated from BV PCR assayanalysis of samples with gold-standard results. BV PCR Result Sample SetBV Status Positive Negative Indeterminate First Sample Group BV Positive98 6 4 (n = 169) BV Negative 3 55 3 Second Sample BV Positive 104 1 5Group (n = 227) BV Negative 10 98 9 Combined Sample BV Positive 202 7 9Group BV Negative 13 153 12 (n = 396)

Example 14 Bacterial Marker Selection for the BV Diagnostic Test

A combination of three BV-positive marker organisms (Atopobium vaginae,BVAB-2, and Megasphaera-1) resulted in a three-marker qPCR testproducing BV diagnostic results in agreement with the conventional goldstandard techniques for diagnosing BV. It was determined that inclusionof at least one positive marker organisms with high sensitivity butlower specificity and one positive marker organism with lowersensitivity but higher specificity resulted in unexpectedly advantageousperformance characteristics of a multi-marker test, such as predictivevalue.

Relative quantitation of large Gram-positive rods, a morphotypeconsistent with a number of peroxide-producing Lactobacillus spp. (suchas, L. crispatus, L. iners, L. jensenii), organisms was previouslyreported as important for maintaining a healthy vaginal environment andtherefore constitutes a significant component (40%) of the total NS.Utility of G. vaginalis and L. crispatus for improving the positivepredictive value of a multi-marker qPCR test was therefore assessed. PCRassays for G. vaginalis and L. crispatus was performed, as discussed inthe earlier examples. The quantity of G. vaginalis, as measured by theqPCR assay, was found to be less predictive of BV than the three markersincluded in the three-marker qPCR test.

L. crispatus was evaluated, as discussed in an earlier example, sincethis organism was previously described as commonly present in low NSsamples across diverse patient populations. In the first sample group,L. crispatus DNA was detected in 42.6% of BV negative samples and onlyin 10.2% of BV positive samples, and median quantitative values of L.crispatus in samples containing this organism were significantly higherin the BV negative population (8.9×10⁷ copies/mL versus 4.1×10⁴copies/mL; p<0.01), consistent with earlier reports that the presence ofthis organism is inversely associated with the presence of BV.Examination of the results for other marker organisms in L.crispatus-positive samples, however, unexpectedly revealed that in onlya single instance was L. crispatus detected in a BV negative sample thatwas scored as positive based on the combination of A. vaginae, BVAB-2,and Megasphaera-1 qPCR results.

In addition, high L. crispatus DNA levels were strongly correlated withthe absence of significant concentrations of positive predictive markerorganisms. No samples in the first sample set containing an L. crispatusconcentration of >5.1×10⁵ copies/mL (n=23) generated a composite BV PCRscore in the BV-positive range. Unexpectedly, it was found the inclusionof Lactobacillus organism in the final assay design would not,therefore, have improved the accuracy of positive results. The datareported herein showed that molecular determination of BV can beachieved using positive predictive markers, thus resulting in a simplermulti-marker test. It was previously documented that the significance ofhydrogen peroxide-producing Lactobacillus species to the overall vaginalmicroflora of healthy women differs considerably based on ethnicbackground. Depending on the ethnic background of the patient and/orother factors, variations of multi-marker tests may include or excludenegative predictive markers, such as L. crispatus.

Example 15 Flexible Adjustments of the Multi-Marker qPCR Test andAssessment of the Performance Characteristics

A three-marker multiplexed qPCR test described herein allowed asemi-quantitative assessment of the DNA concentrations of key positivepredictive markers, maintaining the probative advantage of classifyingsamples by concentration afforded by qPCR, but doing so in a simplifiedand highly reproducible assay format. The classification boundariesdescribed herein were based on the frequency distribution data for BVmarkers in a sample set, as illustrated in shown in FIG. 1.Classification of vaginal populations based on assignment of a numericalscore directly related to critical concentrations of marker organismsunexpectedly resulted in a multi-marker test having improved performancecharacteristics, such as predictive value. However, these classificationboundaries can be changed or adjusted for a particular sample set basedon the statistical data in order to achieve improvements in performancecharacteristics in a particular population.

One advantage of the multi-marker tests described herein is that, sincethey generates results on a discrete numerical scale, the performancecharacteristics of the test in any given population can be estimated bycomparing the frequency distribution of composite scores in thatpopulation with the accuracy of each score derived from the datapresented here. Based on the analysis of the experimental datasummarized in the examples presented herein, in which a score of 0 had anegative predictive value of 97.6% (125/128), whilst a score of 5 or 6had a positive predictive value of 99.2% (123/124), it can be understoodthat the proportion of samples in a population generating these threevalues strongly influences the overall predictive value of the amulti-marker qPCR test described herein.

The frequency distribution of composite scores generated by samplessubmitted for the assay during the first two months after itsintroduction into routine testing were examined, and this examinationdemonstrated that in this unselected clinical population with aprevalence of BV (as determined by BV PCR) of 26.3%, and anindeterminate rate of 6.2%, 81.2% of samples tested generated scores of0, 5, or 6, resulting in estimated positive and negative predictivevalues of 95.1% and 96.8%, respectively. An ability to assessperformance characteristics of the multi-marker qPCR test in a givenpopulation allows for advantageously improved clinically meaningfulinterpretation of the test results, as compared to previously known BVtests. Also, the performance characteristics of the multi-marker qPCRtest can be compared to other tests, this allowing the clinicians toselect the most advantageous test for a particular situation.

Data generated based on the combined sample set and summarized in Table8 indicated a sensitivity and specificity for Affirm™ test of 89.9% and71.1%, and for the three-marker qPCR test of 96.7% and 92.2%,respectively. Based on these data, predictive values were calculated forAffirm™ and three-marker qPCR test for hypothetical populations withdifferent BV prevalence. The results are shown in Table 9.

TABLE 8 Affirm ™ test performance evaluated with respect to thegold-standard BV determination Gold standard results Affirm ™ testAffirm ™ test results Negative Positive performance Negative 173 123 5071.10% specificity Positive 218 22 196 89.91% sensitivity

TABLE 9 Calculated predictive value of Affirm and three-marker qPCRtests based on BV prevalence in a hypothetical patient population. BVprevalence in a hypothetical patient Test population Calculatedpredictive value Affirm 40% 67.4% PPV 91.4% NPV 30% 57.1% PPV 94.3% NPV20% 43.4% PPV 96.3% NPV 10% 25.4% PPV 98.3% NPV Three-marker qPCR 40%89.2% PPV 97.7% NPV 30% 84.1% PPV 98.4% NPV 20% 75.7% PPV 99.1% NPV 10%58.1% PPV 99.6% NPV

Depending on the BV prevalence in a hypothetical patient populationwithin the range shown in Table 9 (10%-40%), the advantageous increasein PPV for the three-marker q-PCR test as compared to the Affirm™ test,ranges between approximately 22-33%.

Different arrangements and combinations of the elements and the featuresdescribed herein are possible. Similarly, some features andsubcombinations are useful and may be employed without reference toother features and subcombinations. Embodiments of the invention andexamples have been described for illustrative and not restrictivepurposes, and alternative embodiments will become apparent to readers ofthis patent. Accordingly, the present invention is not limited to theembodiments described above or depicted in the drawings, and variousembodiments and modifications can be made without departing from thescope of the invention.

What is claimed is:
 1. A method of detecting positive marker bacterialvaginosis (BV)-associated bacteria, comprising performing on agynecological sample obtained from a female a polymerase chain reaction(PCR) or a direct nucleic acid assay to detect nucleic acid sequencescharacteristic of the positive marker BV-associated bacteria, whereinthe positive marker BV-associated bacteria comprise BVAB-2,Megasphaera-1, and at least one of Atopobium vaginae or Gardnerellavaginalis.
 2. The method of claim 1, wherein the assay is the PCR assay.3. The method of claim 2, wherein the PCR assay is a real-time PCRassay.
 4. The method of claim 1, wherein the assay is the direct nucleicacid assay.
 5. The method of claim 1, wherein the nucleic acid sequencesare DNA sequences.
 6. The method of claim 1, wherein the nucleic acidsequences characteristic of the positive-marker BV-associated bacteriaare quantified by the assay.
 7. The method of claim 1, wherein thegynecological sample is a vaginal swab, a vaginal mucus sample, avaginal tissue sample or a vaginal cell sample.
 8. The method of claim1, wherein the positive the positive marker BV-associated bacteriacomprise BVAB-2, Megasphaera-1, Atopobium vaginae and Gardnerellavaginalis.
 9. The method of claim 1, wherein the positive the positivemarker BV-associated bacteria comprise BVAB-2, Megasphaera-1 andAtopobium vaginae.
 10. The method of claim 1, wherein the positive thepositive marker BV-associated bacteria comprise BVAB-2, Megasphaera-1and Gardnerella vaginalis.
 11. The method of claim 1, wherein the assayis a multiplex assay.
 12. The method of claim 1, wherein a combinedresult of detecting nucleic acid sequences characteristic of thepositive marker BV-associated bacteria in the gynecological sampledirectly correlates with presence or absence of BV in the female. 13.The method of claim 1, wherein a combined result of detecting nucleicacid sequences characteristic of the positive marker BV-associatedbacteria is probative for vaginal microflora alterations underlying BV.14. The method of claim 1, wherein the gynecological sample is obtainedfrom a female exhibiting vaginitis symptoms.
 15. A method for assessingbacterial vaginosis (BV) status of a female, comprising detecting by apolymerase chain reaction (PCR) or a direct nucleic acid assay nucleicacid sequences characteristic of positive marker BV-associated bacteriain a gynecological sample obtained from the female, wherein the positivemarker BV-associated bacteria comprise BVAB-2, Megasphaera-1, and atleast one of Atopobium vaginae or Gardnerella vaginalis.
 16. The methodof claim 15, wherein the assay is a PCR assay.
 17. The method of claim16, wherein the PCR assay is a real-time PCR assay.
 18. The method ofclaim 15, wherein the assay is the direct nucleic acid assay.
 19. Themethod of claim 15, wherein the nucleic acid sequences are DNAsequences.
 20. The method of claim 15, wherein the nucleic acidsequences characteristic of the positive-marker BV-associated bacteriaare quantified by the assay.
 21. The method of claim 15, wherein thegynecological sample is a vaginal swab, a vaginal mucus sample, avaginal tissue sample or a vaginal cell sample.
 22. The method of claim15, wherein the positive the positive marker BV-associated bacteriacomprise BVAB-2, Megasphaera-1, Atopobium vaginae and Gardnerellavaginalis.
 23. The method of claim 15, wherein the positive the positivemarker BV-associated bacteria comprise BVAB-2, Megasphaera-1 andAtopobium vaginae.
 24. The method of claim 15, wherein the positive thepositive marker BV-associated bacteria comprise BVAB-2, Megasphaera-1and Gardnerella vaginalis.
 25. The method of claim 15, wherein the assayis a multiplex assay.
 26. The method of claim 15, wherein a combinedresult of detecting nucleic acid sequences characteristic of thepositive marker BV-associated bacteria in the gynecological sampledirectly correlates with presence or absence of BV in the female. 27.The method of claim 15, wherein a combined result of detecting nucleicacid sequences characteristic of the positive marker BV-associatedbacteria is probative for vaginal microflora alterations underlying BV.28. The method of claim 15, wherein the gynecological sample is obtainedfrom a female exhibiting vaginitis symptoms.